Simplified Risk Stratification Model for Patients With Waldenström Macroglobulinemia

PURPOSE Patients with Waldenström macroglobulinemia (WM) have disparate outcomes. Newer therapies have emerged since the development of International Prognostic Scoring System, and MYD88L265P mutation is now frequently assessed at diagnosis, warranting reexamination of the prognostic parameters. PATIENTS AND METHODS We reviewed records of 889 treatment-naïve patients with active WM, consecutively seen between January 01, 1996, and December 31, 2017, to identify clinical predictors of overall survival (OS) in univariate analyses. Patients with complete data for the parameters significant on the univariate analyses (n = 341) were included in a multivariable analysis to derive a prognostic model, subsequently validated in a multi-institutional cohort. RESULTS In the derivation cohort (n = 341), age (hazard ratio [HR], 1.9 [95% CI, 1.2 to 2.1]; P = .0009), serum lactate dehydrogenase (LDH) above upper limit of normal (HR, 2.3 [95% CI, 1.3 to 4.5]; P = .007), and serum albumin <3.5 g/dL (HR, 1.5 [95% CI, 0.99 to 2.3]; P = .056) were independently prognostic. By assigning a score of 1 point each to albumin <3.5 g/dL (HR, 1.5) and age 66-75 years (HR 1.4) and 2 points for age >75 years (HR, 2.6) or elevated LDH (HR, 2.3), four groups with distinct outcomes were observed on the basis of the composite scores. Five-year OS was 93% for the low-risk (score 0), 82% for low-intermediate risk (score 1), 69% for intermediate-risk (score 2), and 55% for the high-risk (score ≥3; P < .0001) groups. In the validation cohort (N = 335), the model maintained its prognostic value, with a 5-year OS of 93%, 90%, 75%, and 57% for the four groups, respectively (P < .0001). CONCLUSION Modified Staging System for WM (MSS-WM), utilizing age, albumin, and LDH is a simple, clinically useful, and externally validated prognostic model that reliably risk-stratifies patients with symptomatic WM into four groups with distinct prognosis.


INTRODUCTION
][9][10][11] Robust prognostic models that accurately predict outcomes and potentially aid in rationally developing risk-adapted treatment strategies are needed.
The International Prognostic Scoring System for WM (IPSS-WM) emerged from a collaborative effort to stage patients requiring treatment into three groups on the basis of five parameters: age, platelet count, hemoglobin, beta-2 microglobulin (b2M), and IgM level. 12The original IPSS-WM modeling included patients diagnosed and treated prior to 2002, before the frequent frontline use of chemoimmunotherapy, proteasome inhibitor-based or Bruton tyrosine kinase inhibitor (BTKi)-based regimens, and demonstrated 5-year overall survival (OS) of 87%, 68%, and 36% for the low-, intermediate-, and high-risk groups, respectively. 12The IPSS-WM did not assess the issue of non-WM-related deaths. 13,14The recently proposed, revised (r) IPSS-WM, on the basis of age, lactate dehydrogenase (LDH), albumin, and b2M, addressed some of the deficiencies but did not examine the impact of molecular parameters, including the myeloid differentiation primary response 88 (MYD88) L265P mutation, which is now routinely assessed at diagnosis.Moreover, rIPSS-WM could be only partially replicated in the validation cohort and remains to be broadly adopted. 15Through this study, we examined the performance of rIPSS-WM in treatment-na ïve patients with active WM and propose a refined prognostic model, with external validation in a multi-institutional cohort of patients from the United States and Europe.

METHODS
Following the Institutional Review Board approval, we included patients with active WM, diagnosed between January 01, 1996, and December 31, 2017, and evaluated consecutively at the Mayo Clinic, Rochester (MCR), Minnesota.This study was conducted in accordance with the Declaration of Helsinki.Each center obtained individual informed consent from patients per institutional requirements.Patients with at least 10% bone marrow lymphoplasmacytic infiltration and a circulating monoclonal IgM protein, causing symptoms and/or laboratory abnormalities requiring initiation of therapy per the Consensus Criteria, were considered to have active WM. 16e applied the rIPSS-WM model in patients with data available for all parameters required to assess its utility.We then examined the baseline dichotomized clinical and laboratory parameters affecting OS, with all-cause mortality as the event of interest in the MCR cohort, using a univariate Cox proportional hazard analysis (UVA).To maximize the use of the available data in the setting of varying degree of missing data across variables, the UVA included all patients with available data for the variable under evaluation.This was followed by a multivariate Cox proportional hazard regression analysis (MVA) involving patients with complete data for the variables to identify the independent prognosticators of OS.The variables deemed independently prognostic (P ≤ .1) on the MVA were assigned a score proportional to their hazard ratio (HR), wherein those with comparable HR were assigned equal point(s).Little's test was used to assess whether missingness of the data was completely at random and independent of both the observed and the unobserved data, with the null hypothesis that the data were missing completely at random. 17e cutoffs for the covariates were selected on the basis of previously established thresholds. 12For LDH, the upper limit of normal (ULN) was used as cutoff to ensure generalizability, given the different cutoffs used in the multiinstitutional validation cohort.We used a cohort comprising treatment-na ïve patients with active WM from five institutions (Data Supplement, Table S1 [online only]) to validate our model.The Kaplan-Meier method was utilized for time-to-event analyses and survival was compared using the log-rank test. 18A competing risk analysis was used to validate the model on the basis of the cause of death (cmprsk package, version 2.2-1.1,R). 19Deaths occurring from WM progression, HT, ALH, or WM-directed treatment-associated complications, including therapyrelated myeloid neoplasm, were considered WM-related and deaths from other causes as competing events; patients alive at last follow-up were censored.The discriminatory power of different models and their relative goodness of fit for predictive score was assessed by computing Harrell's concordance index (dynpred package version 0.1.2,R).

RESULTS
We identified a cohort of 889 patients with active WM at MCR who had a median follow-up of 8.2 (95% CI, 7.5 to 9) years.Because we could not validate rIPSS-WM in our data set (reported later), we used the MCR cohort data to generate a new prognostic model.Table 1 2).

Prognostic Model Score Calculation
Owing to comparable HR (Table 2), we assigned a score of 1 point each to serum albumin <3.5 g/dL and age 66-75 years and similarly 2 points each to age >75 years and elevated serum LDH, in accordance with their impact on OS.Using this scoring system, a prognostic model was generated with the composite scores ranging from 0 to 5. Patients with the composite scores of 0, 1, and 2 were assigned to the low-risk (n 5 71, 21%), low-intermediate risk (n 5 110, 32%), and intermediate-risk (n 5 81, 24%) groups, respectively.Owing to similar outcomes for patients with the composite scores of 3 to 5 and small sizes of the subcohorts with the composite scores of 4 (n 5 14) and 5 (n 5 5), these subcohorts were integrated to generate the high-risk group (n 5 79, 23%).The estimated median OS for this derivation cohort with complete data (n 5 341) was 9.9 (95% CI, 8.5 to 11.4) years.The estimated median OS was 14.6 (95% CI, 9.1 to NR) years, 11.2 (95% CI, 9.1 to 15.2) years, 8.3 (95% CI, 6.4 to 12.2) years, and 5.5 (95% CI, 3.9 to 11) years, for the low-risk,  S2).
To assess for any possible selection bias arising from the exclusion of the patients with unavailable data in the MCR cohort, we compared the baseline characteristics and outcome of patients with and without the missing data.Barring a higher proportion of patients with age >65 years in the cohort with the incomplete data (Data Supplement, Table S3), the characteristics were comparable, as was the OS of the two cohorts (Data Supplement, Fig S2).Additionally, data missing at the level of each variable did not affect survival (Data Supplement, Fig S3).The proportion of patients with missing data across the different time periods was similar and is demonstrated in the Data Supplement (Table S4).In missing data analysis, the inability to reject the null hypothesis (P 5 .268)provided sufficient evidence to indicate that the data were missing completely at random.

Prognostic Model Validation
We

Performance of Existing Prognostic Models for WM
The rIPSS-WM model was examined in our MCR (derivation) and validation cohorts. 15 S6).

Treatment Patterns
Single-agent rituximab was the commonest frontline therapy (Data Supplement, Table S7) used (n 5 277, 33%) in the derivation cohort, followed by rituximab-alkylator combinations (n 5 234; 28%) and alkylator monotherapy (n 5 167; 20%).A steady increase in the rituximab-alkylator combination as the frontline therapy was observed over the study period: However, within the study time frame, only a small fraction of the evaluable patients (n 5 57, 17%) were exposed to BTKi, precluding the assessment of MSS-WM in this subset.

DISCUSSION
On the basis of our findings, we propose a simpler, externally validated staging system, the MSS-WM, 40 which riskstratifies patients into four distinct groups, demonstrating 5-year OS rates ranging from 55% to 93% and clearly delineating a subset with an outstanding outcome, despite the lack of curative therapies.
Low serum albumin is a marker of patients' overall health and poor nutritional status, reflecting reduced hepatic synthesis, mediated in part by high levels of circulating interleukin-6 and other cytokines in WM, and is independently prognostic. 20,21Additionally, low albumin may occur in ALH, a complication of WM with distinctly poorer outcomes. 22Not surprisingly, elevated LDH, a marker of high cell turnover and aggressive disease biology, which has been incorporated in other staging systems of related lymphoproliferative malignancies, emerged as independently prognostic. 13,23 elderly patients (older than 75 years at the time of diagnosis of WM) compared with the age-and sex-matched US population. 24Previous studies with limited strength and reproducibility have identified various prognostic factors, including hemoglobin, b2M, and IgM concentration, among others, paving the way for the IPSS-WM, the most consistently used prognostic tool since its development. 23,25,26Many of these variables were, however, not prognostic in our cohort.
The One of the limitations of the IPSS-WM model was the lack of data regarding the cause of death and its impact.In the rIPSS-WM modeling, 22% deaths were WM-unrelated. 13In our cohort, 37% of the deaths were deemed WM-unrelated.Therefore, given the advanced age at presentation, we performed a competing risk analysis to accurately assess OS and the MSS-WM model held its discriminative ability.
The rates of ALH and HT, complications typically associated with inferior survival in patients with WM, 22,27 were similar across the four risk groups (Data Supplement, Table S2) and comparable with the previously reported data, making them unlikely to skew outcomes. 28,29Mirroring previous studies, nearly one in five patients with active WM in our cohort had antecedent smoldering WM. 30,31 To avoid the potential impact of the lead-time bias arising from an incidental diagnosis, we estimated OS from the development of active/symptomatic WM rather than the diagnosis of smoldering WM.
3][34] However, this molecular information was not examined for the creation of the rIPSS-WM model.In our large derivation and validation cohorts, the locally assessed MYD88 L265P genotype did not significantly influence outcomes.Delineating the impact of a specific therapy/ regimen on survival is challenging as, eventually, a sizable proportion of survivors receive most of the frequently used therapies during the relapsing-remitting course of WM.Although exposure to rituximab as monotherapy or combination improved survival, this gain may be partly attributable to the non-rituximab-exposed cohort belonging to an earlier era, with inferior supportive care and limited access to novel effective treatments.Nonetheless, our rituximab nonexposed cohort, accounting for a small subset, did not affect the generalizability of MSS-WM.
Recognizing the inherent limitations of a retrospective analysis, we attempted to overcome the biases introduced because of the unavailable data by comparing outcomes and the baseline characteristics of the cohorts with and without the missing data.Our findings were largely similar in the two cohorts.Data regarding the CXC motif chemokine receptor 4 (CXCR4) mutation, associated with resistance to certain treatments, were absent in most patients, precluding its incorporation into the model.Regardless, in contrast to the MYD88 L265P assessment, incorporation of CXCR4 mutation(s) status would be challenging because of the costs and complexity of the assay, involving more than 40 different mutations, and consequently sparse testing outside of academic centers. 35,36In the future, a targeted-approach, using a polymerase chain reaction-based assay to examine the commonest mutation, CXCR4 S338X , may render the test results more readily available to augment the proposed model, if found to be independently prognostic.Owing to the shorter follow-up since the approval of the BTKi for WM, a small fraction of patients in our cohort have received this class of agents as primary therapy.Therefore, the applicability of MSS-WM in the BTKi era would require reexamination in the future, in a large cohort with a protracted follow-up.Additionally, MSS-WM merits prospective validation in clinical trials and evaluation as a prognostic tool to guide clinical decision making.
Notwithstanding these limitations, MSS-WM represents a robust multi-institutional effort, involving a large cohort, with a respectable follow-up.Incorporation of the routinely obtained variables enhances its applicability in clinical practice.[39] In summary, MSS-WM is a simple, externally validated, robust, risk-stratification model based on patients' age, serum albumin, and serum LDH, which reliably captures the prognosis of previously untreated patients with active WM.
, low-intermediate risk, intermediate-risk, and high-risk cohorts, respectively (P < .0001,Fig2).Similar to the derivation cohort, the MYD88 genotype did not significantly affect the OS of the validation cohort (5-year OS of 64% v 81% for the MYD88 L265P and MYD88 WT genotype, respectively, P 5 .10).
46), and very high-risk groups (n 5 27), with the respective 5-year OS rates of 96%, 76%, 72%, 77%, and 32%.Although the concordance index of 0.67 (95% CI, 0.61 to 0.73) for the rIPSS-WM model was similar to that of the derivation cohort of MSS-WM model (concordance index 0.68, 95% CI, 0.63 to 0.73), the survival curves of the patients in the low-, intermediate-, and high-risk groups were overlapping (Fig3A).Similarly, in the validation cohort, Patients with available data (n 5 241) in the derivation cohort were risk stratified into very low-(n 5 46), low-(n 5 64), intermediate-(n 5 58), high-(n 5 a sizable proportion of patients from the IPSS-WM intermediate group were reclassified in the MSS-WM model (Fig 4).The Data Supplement (Fig S5 and TableS5) shows the redistribution of patients and the distinct outcomes of the patients who were reclassified by the MSS-WM within each stratum of the IPSS-WM (Fig S6).By contrast, the IPSS-WM did not identify any subcohorts with dissimilar outcomes within each MSS-WM cohort (data not shown).FIG 2. Validation of the MSS-WM prognostic model in an external cohort reveals a 5-year overall survival of 93%, 90%, 75%, and 57% for the low-risk, low-intermediate risk, intermediate-risk, and high-risk cohorts, respectively.MSS, Modified Staging System for WM; WM, Waldenström macroglobulinemia.Cause of Death in WMAmong 360 (40%) patient deaths in the derivation cohort, the cause was attributable to WM in 230 (63.9%), with unrelated second primary malignancies (n 5 29; 8%), cardiovascular (n 5 16; 5%) and neurologic issues (n 5 16; 5%) being the most frequent causes for non-WM related deaths.The cause was unclear in 43 (12%) patients but A Sankey diagram showing a high-level view of the redistribution of the patients from the IPSS-WM risk categories to the MSS-WM risk groups: Among 220 patients, a substantial proportion from the highrisk IPSS-WM (65%, 57/88) were downstaged as low-, low-intermediate, or intermediate-risk by MSS-WM, whereas 44% (16/36) of patients in low-risk IPSS-WM were upstaged as low-intermediate or intermediaterisk by MSS-WM.Similarly, a sizable proportion of patients from the IPSS-WM intermediate group were reclassified to the MSS low (17%, 16/96) and MSS high (19%, 18/96)-risk groups.Int, intermediate risk; IPSS, International Prognostic Staging System for WM; Low-Int, low-intermediate risk; MSS, Modified Staging System for WM; WM, Waldenström macroglobulinemia.
Similar to the previous studies, age remained a crucial determinant of prognosis.Strikingly, even among patients with age >75 years, most deaths were deemed WM-related.These findings are consistent with the previous data showing a reduced survival rate for Journal of Clinical Oncology ascopubs.org/journal/jco| Volume 42, Issue 21 | 2533